class_docstr: GDELT dataset for event-based temporal graph
  
  The Global Database of Events, Language, and Tone (GDELT) dataset.
  This contains events happend all over the world (ie every protest held
  anywhere in Russia on a given day is collapsed to a single entry).
  This Dataset consists ofevents collected from 1/1/2018 to 1/31/2018
  (15 minutes time granularity).
  
  Reference:
  
      - `Recurrent Event Network for Reasoning over Temporal Knowledge Graphs <https://arxiv.org/abs/1904.05530>`_
      - `The Global Database of Events, Language, and Tone (GDELT) <https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/28075>`_
  
  Statistics:
  
  - Train examples: 2,304
  - Valid examples: 288
  - Test examples: 384
  
  Parameters
  ----------
  mode : str
      Must be one of ('train', 'valid', 'test'). Default: 'train'
  raw_dir : str
      Raw file directory to download/contains the input data directory.
      Default: ~/.dgl/
  force_reload : bool
      Whether to reload the dataset. Default: False
  verbose : bool
      Whether to print out progress information. Default: True.
  transform : callable, optional
      A transform that takes in a :class:`~dgl.DGLGraph` object and returns
      a transformed version. The :class:`~dgl.DGLGraph` object will be
      transformed before every access.
  
  Attributes
  ----------
  start_time : int
      Start time of the temporal graph
  end_time : int
      End time of the temporal graph
  is_temporal : bool
      Does the dataset contain temporal graphs
  
  Examples
  ----------
  >>> # get train, valid, test dataset
  >>> train_data = GDELTDataset()
  >>> valid_data = GDELTDataset(mode='valid')
  >>> test_data = GDELTDataset(mode='test')
  >>>
  >>> # length of train set
  >>> train_size = len(train_data)
  >>>
  >>> for g in train_data:
  ....    e_feat = g.edata['rel_type']
  ....    # your code here
  ....
  >>>
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code: def load(self):
      info = load_info(self.info_path)
      self.data, self.time_index, self._start_time, self._end_time = (
          info["data"],
          info["time_index"],
          info["start_time"],
          info["end_time"],
      )
  
file_path: dgl/python/dgl/data/gdelt.py
imports: import os
  import numpy
  from ..None import backend
  from ..convert import graph
  from .dgl_dataset import DGLBuiltinDataset
  from .utils import _get_dgl_url, load_info, loadtxt, save_info
label_desc: Use image node_id 6 for calling the GDELTDataset obj's underlying member method code with example usage: obj.load() without return types